Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov 4:12:755124.
doi: 10.3389/fphys.2021.755124. eCollection 2021.

Differential Effects of 'Vaping' on Lipid and Glucose Profiles and Liver Metabolic Markers in Obese Versus Non-obese Mice

Affiliations

Differential Effects of 'Vaping' on Lipid and Glucose Profiles and Liver Metabolic Markers in Obese Versus Non-obese Mice

Hui Chen et al. Front Physiol. .

Abstract

Tobacco smoking increases the risk of metabolic disorders due to the combination of harmful chemicals, whereas pure nicotine can improve glucose tolerance. E-cigarette vapour contains nicotine and some of the harmful chemicals found in cigarette smoke at lower levels. To investigate how e-vapour affects metabolic profiles, male Balb/c mice were exposed to a high-fat diet (HFD, 43% fat, 20kJ/g) for 16weeks, and e-vapour in the last 6weeks. HFD alone doubled fat mass and caused dyslipidaemia and glucose intolerance. E-vapour reduced fat mass in HFD-fed mice; only nicotine-containing e-vapour improved glucose tolerance. In chow-fed mice, e-vapour increased lipid content in both blood and liver. Changes in liver metabolic markers may be adaptive responses rather than causal. Future studies can investigate how e-vapour differentially affects metabolic profiles with different diets.

Keywords: abdominal obesity; free fatty acid; glucose tolerance; liver; triglycerides.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Lipid metabolic markers in the liver. Protein level of FASN (A), mRNA expression of ATGL (B) and CPT1a (C) in mice fed a HFD with or without the exposure to e-vapour. The results are expressed as mean±SEM, n=5–8. Data were analysed by two-way ANOVA followed by Fisher’s least significant difference (LSD) post-hoc tests. A conditional t-test for non-overlap of value distributions was performed between the control (Chow+sham or HFD+sham) and interventional groups. **p<0.01 diet effect, δδp<0.01 e-vapour exposure effect; tp<0.05 vs. Chow+Sham by conditional t-test, #p<0.05, ##p<0.01 vs. HFD+Sham, p<0.05 vs. Chow+e-cig18mg and ‡‡p<0.01 vs. Chow+e-cig0. ATGL, adipose triglyceride lipase; CPT, carnitine palmitoyltransferase; and FASN, fatty acid synthase.
Figure 2
Figure 2
Glucose level during intraperitoneal glucose tolerance test (IPGTT, A) and mRNA expression of markers of inflammation [TNF-α (B), IL-1β (C)], fibrosis (Col1a1, D), insulin sensing (PPARγ, E), glucose transporter [Glut2 (F), Glut4 (G)] and gluconeogenesis [PEPCK (H), FOXO1 (I)] in the liver. The results are expressed as mean±SEM, n=5–8. Data were analysed by two-way ANOVA followed by Fisher’s least significant difference (LSD) post-hoc tests. θp<0.05 Chow+e-cig0 vs. HFD+e-cig0; ϕp<0.01 Chow+sham vs. HFD+sham; φp<0.05 Chow+sham vs. HFD+sham; Chow+e-cig18 vs. HFD+e-cig18; *p<0.05, **p<0.01 diet effect, δp<0.05 e-vapour exposure effect; γp<0.05, γγp<0.01 vs. Chow+sham; and #p<0.05 vs. HFD+Sham, p<0.05; ††p<0.01 vs. Chow+e-cig18 and p<0.05 vs. Chow+e-cig0. Col1a1, collagen 1a1; FOXO1, Forkhead box protein O1; Glut, glucose transporter; PEPCK, phosphoenolpyruvate carboxykinase; and PPAR, Peroxisome proliferator-activated receptors.

References

    1. Alpert H. R., Agaku I. T., Connolly G. N. (2015). A study of pyrazines in cigarettes and how additives might be used to enhance tobacco addiction. Tob. Control. 25, 444–450. doi: 10.1136/tobaccocontrol-2014-051943, PMID: - DOI - PMC - PubMed
    1. Bustin S. A., Benes V., Garson J. A., Hellemans J., Huggett J., Kubista M., et al. . (2009). The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 55, 611–622. doi: 10.1373/clinchem.2008.112797, PMID: - DOI - PubMed
    1. Chen H., Hansen M. J., Jones J. E., Vlahos R., Anderson G., Morris M. J. (2007). Detrimental metabolic effects of combining long term cigarette smoke exposure and high-fat diet in mice. Am. J. Physiol. Endocrinol. Metab. 293, E1564–E1571. doi: 10.1152/ajpendo.00442.2007, PMID: - DOI - PubMed
    1. Chen H., Li G., Chan Y. L., Chapman D. G., Sukjamnong S., Nguyen T., et al. . (2018a). Maternal e-cigarette exposure in mice alters DNA methylation and lung cytokine expression in offspring. Am. J. Respir. Cell Mol. Biol. 58, 366–377. doi: 10.1165/rcmb.2017-0206RC, PMID: - DOI - PubMed
    1. Chen H., Ng J. P. M., Bishop D. P., Milthorpe B. K., Valenzuela S. M. (2018b). Gold nanoparticles as cell regulators: beneficial effects of gold nanoparticles on the metabolic profile of mice with pre-existing obesity. J. Nanobiotechnol. 16:88. doi: 10.1186/s12951-018-0414-6, PMID: - DOI - PMC - PubMed

LinkOut - more resources